基于RSSI和融合智能优化算法的无线传感器网络定位算法  

Wireless Sensor Networks Locating Algorithm Based on RSSI and Hybrid Intelligent Optimization Algorithm

作　　者：张先超[1] 刘兴长[1] 钟一洋[2] 张春园[1] 

机构地区：[1]后勤工程学院后勤信息与军事物流工程系,重庆401311 [2]后勤工程学院学员旅,重庆401311

出　　处：《重庆理工大学学报（自然科学）》2015年第9期116-121,共6页Journal of Chongqing University of Technology：Natural Science

基　　金：重庆市自然科学基金计划项目(CSTC;2009BB2179)

摘　　要：针对基于单一的粒子群或人工鱼群的无线传感器网络定位算法性能存在缺陷的问题,提出一种基于粒子群和人工鱼群融合优化算法的无线传感器网络定位算法。采用RSSI测距,利用测得的距离信息和锚节点位置信息建立适应度函数。在迭代寻优阶段,采用粒子群和人工鱼群协同进化的策略,同时对性能较差的个体进行变异操作,用较优的群体对整个种群进行更新。仿真结果表明:该定位算法具有更优越的性能,加快了收敛速度,提高了定位精度和稳定性。To the question that the localization algorithm in wireless sensor network which was based on the single particle swarm algorithm or artificial fish swarm algorithm remains some performance pit- falls, this paper put forward a localization algorithm in wireless sensor network which was an optimal fusion algorithm based on particle swarm algorithm and artificial fish swarm algorithm. RSSI was a- dopted by the localization algorithm and utilized the range information and anchor nodes location infor- mation which measured by RSSI to build fitness function. At the stage of iterative refinement, it a- dopted the strategy that particle swarm and artificial fish co-evolutionary strategy. Meanwhile, it car- ried out mutation operation to the poor performance individual, and then made use of the better group to update the whole group. The simulations reveal that the localization algorithm possesses superior performance, accelerates convergence velocity and improves location accuracy as well as stability.

关 键 词：无线传感器网络 粒子群 人工鱼群 定位精度 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]